docs/examples/driver_examples/Qcodes example with Stanford SR86x with buffered readout.ipynb

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   "source": [
    "# QCoDeS Example with Standford Research SR86x Lock-in Amplifier with Buffered Readout\n",
    "\n",
    "This notebook provides a code example of usage of the driver for Standford Research SR86x lock-in amplifier. Special attention is given to reading the captured data from the lock-in's internal buffer.\n",
    "\n",
    "This notebook covers several capturing modes including starting capture at trigger, and capturing one sample per trigger. For the purpose of this example, a Tektronix AWG5208 will be used to send trigger signals. One can also use `qcodes.instrument_drivers.QuTech.IVVI` with its `trigger` method, or else."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up infrastructure for the examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "# Useful utilities\n",
    "import time\n",
    "import matplotlib.pyplot as plt \n",
    "import numpy\n",
    "from pprint import pprint  # for pretty printing lists and dictionaries\n",
    "\n",
    "# QCoDeS\n",
    "import qcodes\n",
    "\n",
    "# Drivers\n",
    "from qcodes.instrument_drivers.stanford_research.SR860 \\\n",
    "    import SR860  # the lock-in amplifier\n",
    "from qcodes.instrument_drivers.tektronix.AWG5208 \\\n",
    "    import AWG5208  # used for sending trigger signals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize the driver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: Stanford_Research_Systems SR860 (serial:003223, firmware:V1.47) in 0.25s\n"
     ]
    }
   ],
   "source": [
    "lockin = SR860(\"lockin\", \"GPIB0::4::INSTR\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basics of reading values from the lock-in\n",
    "\n",
    "Lock-in amplifier measures a number of values. The most frequently used ones are available in the driver directly as QCODES parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X = 3.1690581181e-07\n",
      "Y = 2.9734803775e-07\n",
      "R = 4.2155235747e-07\n",
      "P = 45.936515808\n"
     ]
    }
   ],
   "source": [
    "print(f'X = { lockin.X() }')\n",
    "print(f'Y = { lockin.Y() }')\n",
    "print(f'R = { lockin.R() }')\n",
    "print(f'P = { lockin.P() }')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Actually, the full list of values (or 'parameters', not to be confused with QCODES parameters) that the lock-in amplifier measures is available in the following dictionary (refer to the page 132 of the instrument's manual for more information):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['X',\n",
      " 'Y',\n",
      " 'R',\n",
      " 'P',\n",
      " 'aux_in1',\n",
      " 'aux_in2',\n",
      " 'aux_in3',\n",
      " 'aux_in4',\n",
      " 'Xnoise',\n",
      " 'Ynoise',\n",
      " 'aux_out1',\n",
      " 'aux_out2',\n",
      " 'phase',\n",
      " 'amplitude',\n",
      " 'sine_outdc',\n",
      " 'frequency',\n",
      " 'frequency_ext']\n"
     ]
    }
   ],
   "source": [
    "pprint(list(lockin.PARAMETER_NAMES.keys()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the `get_values` method of the driver to obtain values of 2 or 3 of those parameters. The values that are returned by this method are guaranteed to be coming from the same measurement, as opposed to requesting values sequentially by calling `lockin.X()` and then `lockin.Y()`. The method returns a tuple of values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-2.1813903572e-07, 1.6225968125e-07, 3.1462531069e-07)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.get_values('X', 'Y', 'Xnoise')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.696416459e-07, 152.20687866)"
      ]
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.get_values('R', 'P')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data channels\n",
    "\n",
    "Lock-in amplifier has a notion of data channels. Each data channel can be assigned to a measured parameter mentioned above. Each data channel is being displayed on the insturment's screen, and has a corresponding color.\n",
    "\n",
    "Let's list the data channels using the `data_channels` list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lock-in amplifier has the following data channels:\n",
      "DAT1 (green)\n",
      "DAT2 (blue)\n",
      "DAT3 (yellow)\n",
      "DAT4 (orange)\n"
     ]
    }
   ],
   "source": [
    "msg = f'Lock-in amplifier has the following data channels:\\n'\n",
    "msg += '\\n'.join([f'{dch.cmd_id_name} ({dch.color})' for dch in lockin.data_channels])\n",
    "print(msg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These channels are also accessible individually from the lock-in amplifier driver instance with `data_channel_<i>` attributes.\n",
    "\n",
    "Each of the channels has a `color`, `cmd_id` that is used in VISA commands, and `cmd_id_name` that can be (but is not) used in VISA commands, and is just there for reference.\n",
    "\n",
    "Most importantly, each data channel has an `assigned_parameter` to it. The available parameter are coming from the same list of parameters from above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'aux_in3'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.data_channel_3.assigned_parameter('aux_in3')\n",
    "lockin.data_channel_3.assigned_parameter()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main feature of the data channels is that the lock-in amplifier has commands to retrieve all of their values at once. This feature is similar to `get_values` method, but instead of specifying the parameter names, the values of the data channels are returned.\n",
    "\n",
    "`get_data_channels_values` method returns a tuple of the values of the data channels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.3243408148e-07, -1.4647376645e-07, -0.00053787231445, -132.11825562)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.get_data_channels_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to see which are the assigned parameters for all the data channels, `get_data_channels_parameters` method can be used. Note that this method has a keyword argument `query_instrument` that allows you to choose not to query the values from the instrument in order to save time on VISA communication."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('X', 'Y', 'aux_in3', 'P')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.get_data_channels_parameters()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, a convenience method available that returns a dictionary of data channels assigned parameters with the associated values. Note that this method also has a keyword argument `requery_names` that allows you to choose whether the assigned parameter names are queried from the instrument. In this case, by default the names are not queried."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'P': -95.362594604,\n",
       " 'X': -3.9464794099e-08,\n",
       " 'Y': -4.204223103e-07,\n",
       " 'aux_in3': -0.00045776367188}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lockin.get_data_channels_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up for the buffer readout examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set capture configuration\n",
    "\n",
    "The lock-in needs to know what values shall be captured. Let's capture \"X\" and \"Y\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "lockin.input_config('a')\n",
    "lockin.buffer.capture_config('X,Y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set lock-in parameters\n",
    "\n",
    "Let's tune the lock-in so that it measures something reasonable. Let's not attach any cables to the lock-in, and try to perform a measurement of the noise that the instrument is capturing. The most obvious noise source is the grid, 50 Hz, hence let's set the frequency of the lock-in amplifier somewhere below that frequency to see modulations instead of a flat value that we could have measured at 50 Hz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "lockin.input_range(10e-3)  # V\n",
    "\n",
    "lockin.sensitivity(500e-3)  # V\n",
    "lockin.frequency(27.3645)  # Hz\n",
    "lockin.time_constant(10e-3)  # s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize AWG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: TEKTRONIX AWG5208 (serial:B020205, firmware:FV:6.0.0242.0) in 0.12s\n"
     ]
    }
   ],
   "source": [
    "awg = AWG5208(\"awg\", address='TCPIP0::169.254.254.84::inst0::INSTR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One-shot immediate capture\n",
    "\n",
    "We are going to capture a number of data points (also referred to as samples) at a capture rate, retrieve data from the buffer, and plot it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set capture rate\n",
    "\n",
    "The lock-in will be capturing data at some rate. Let's set this rate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Capture rate is set to 1220.703125\n"
     ]
    }
   ],
   "source": [
    "lockin.buffer.capture_rate(1220.7)\n",
    "print(f\"Capture rate is set to {lockin.buffer.capture_rate()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In case you want to capture data at a maximum possible rate, but you do not remember the value of the maximum possible capture rate, the convenient `set_capture_rate_to_maximum` method can be used: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Capture rate is set to its maximum: 39062.5\n"
     ]
    }
   ],
   "source": [
    "lockin.buffer.set_capture_rate_to_maximum()\n",
    "print(f\"Capture rate is set to its maximum: {lockin.buffer.capture_rate()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capture data\n",
    "\n",
    "Now let's acquire some data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of acquired X data points is 678\n",
      "The number of acquired Y data points is 678\n"
     ]
    }
   ],
   "source": [
    "sample_count = 678\n",
    "\n",
    "# Set the capture length (which is a portion of the buffer size) \n",
    "# to fit the number of samples that we want to capture.\n",
    "# For more information about the maximum buffer size, \n",
    "# and other buffer-related properties, refer to the instrument manual.\n",
    "lockin.buffer.set_capture_length_to_fit_samples(sample_count)\n",
    "\n",
    "# Start capturing data immediately, \n",
    "# and without overwriting the buffer in case it gets full.\n",
    "# For more information about the capture modes, refer to the instrument manual.\n",
    "lockin.buffer.start_capture(\"ONE\", \"IMM\")\n",
    "\n",
    "# We call this blocking method to wait until \n",
    "# the requested number of samples is captured.\n",
    "lockin.buffer.wait_until_samples_captured(sample_count)\n",
    "\n",
    "# Stop capturing.\n",
    "lockin.buffer.stop_capture()\n",
    "\n",
    "# Retrieve the data from the buffer.\n",
    "# The returned data is a dictionary where keys are names of the variables\n",
    "# from the capture config, and values are the captured values.\n",
    "data = lockin.buffer.get_capture_data(sample_count)\n",
    "\n",
    "print(f\"The number of acquired X data points is {len(data['X'])}\")\n",
    "print(f\"The number of acquired Y data points is {len(data['Y'])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, the measurement code from above is encapsulated into a convenient `capture_samples` method of the lock-in buffer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "data = lockin.buffer.capture_samples(sample_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot the captured data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
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       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size to be more convenient then the defaults\n",
    "fig = plt.figure(figsize=(6, 3))\n",
    "\n",
    "# plot values of all the captured variables\n",
    "for var_name in data:\n",
    "    plt.plot(data[var_name], label=var_name)\n",
    "plt.xlabel(\"Sample, #\")\n",
    "plt.ylabel(\"Measured value, V\")\n",
    "\n",
    "plt.legend()  # show legend\n",
    "plt.tight_layout()  # adjust the figure so that all the labels fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Access captured data via Parameter interface\n",
    "\n",
    "The SR86x driver has the capture variables (X, Y, R, theta) as QCoDeS Parameters in the buffer. This allows to use `lockin.buffer.X.get()` syntax to retrieve the captured data. Beware that it is necessary that the `lockin.buffer.get_capture_data` method has been called before retrieving data via Parameters (in other words, `lockin.buffer.X.get()` does not initiate a new capture, it just returns the latest captured data).\n",
    "\n",
    "For the sake of demonstration, let's plot the captured data again, but now using the Parameters (notice that this plot contains the same data as the one above):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size to be more convenient then the defaults\n",
    "fig = plt.figure(figsize=(6, 3))\n",
    "\n",
    "# plot values of all the captured variables\n",
    "plt.plot(lockin.buffer.X.get(), label='X')\n",
    "plt.plot(lockin.buffer.Y.get(), label='Y')\n",
    "plt.xlabel(\"Sample, #\")\n",
    "plt.ylabel(\"Measured value, V\")\n",
    "\n",
    "plt.legend()  # show legend\n",
    "plt.tight_layout()  # adjust the figure so that all the labels fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Capture after trigger is sent\n",
    "\n",
    "In this example, we are going to initiate data capture via a trigger signal. Lock-in amplifier SR860 reacts on the falling edge of the trigger signal. We are going to use a marker of an AWG channel to send the trigger signal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup AWG to emit a simple trigger signal\n",
    "\n",
    "The following code is specific to the AWG5208 that is used in this example. One is welcome to use waveform generation frameworks like `broadbean` rather than the low-level kind of interaction with the AWG driver below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "awg.sample_rate(3000)  # S/s\n",
    "\n",
    "# Create a waveform where the analog channel plays 0s,\n",
    "# while the marker channel plays a falling edge from 1 to 0.\n",
    "waveform_ch1 = numpy.zeros((2, 3000))  # the waveform will have a length of 1s\n",
    "                                       # (3000 samples for 3000 S/s sample rate)\n",
    "waveform_ch1[1, :-1500] = 1  # falling from 1 to 0 (a.u.), \n",
    "                             # at 0.5s after the start of the waveform\n",
    "elements = numpy.array([waveform_ch1])  # we only have one element in the sequence\n",
    "waveforms = numpy.array([elements])  # we will use only 1 channel\n",
    "\n",
    "# Create a sequence file from the \"waveform\" array\n",
    "seq_name = 'single_trigger_marker_1'\n",
    "seqx = awg.makeSEQXFile(\n",
    "    trig_waits=[0], nreps=[1], event_jumps=[0], event_jump_to=[0], go_to=[1],\n",
    "    wfms=waveforms, amplitudes=[1.0], seqname=seq_name)\n",
    "\n",
    "# Send the sequence file to AWG internal disk\n",
    "seqx_file_name = seq_name + '.seqx'\n",
    "awg.sendSEQXFile(seqx, seqx_file_name)\n",
    "\n",
    "awg.clearSequenceList()\n",
    "awg.clearWaveformList()\n",
    "\n",
    "# Load the sequence file from AWG internal disk\n",
    "awg.loadSEQXFile(seqx_file_name)\n",
    "\n",
    "# Full resolution of the AWG channel is 16 bits for AWG5208,\n",
    "# but we take 1 bit for the marker channel\n",
    "awg.ch1.resolution = 16 - 1\n",
    "\n",
    "awg.ch1.awg_amplitude(1)  # V\n",
    "\n",
    "# Load a particular sequence to the channel\n",
    "awg.ch1.setSequenceTrack(seq_name, 0)\n",
    "# Assign a loaded waveform to the channel\n",
    "awg.ch1.setWaveform(awg.waveformList[0])\n",
    "\n",
    "# Set the marker's high as high as possible \n",
    "# so that the lock-in detects the falling edge\n",
    "awg.ch1.marker1_high(1.75)  # V\n",
    "awg.ch1.marker1_low(0)  # V\n",
    "\n",
    "awg.ch1.state(1)  # turns the channel \"on\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set capture rate\n",
    "\n",
    "Even though we will be triggering the capture via trigger, the lock-in will still be capturing data at some rate. Let's set this rate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "lockin.buffer.capture_rate(4882.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capture data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of acquired X data points is 321\n",
      "The number of acquired Y data points is 321\n"
     ]
    }
   ],
   "source": [
    "sample_count = 321\n",
    "\n",
    "# Set the capture length (which is a portion of the buffer size) \n",
    "# to fit the number of samples that we want to acquire.\n",
    "# For more information about the maximum buffer size, \n",
    "# and other buffer-related properties, refer to the instrument manual.\n",
    "lockin.buffer.set_capture_length_to_fit_samples(sample_count)\n",
    "\n",
    "# Start capturing data when a trigger signal is recieved, \n",
    "# and without overwriting the buffer in case it gets full.\n",
    "# This basically arms the lock-in amplifier.\n",
    "# For more information about the capture modes, refer to the instrument manual.\n",
    "lockin.buffer.start_capture(\"ONE\", \"TRIG\")\n",
    "\n",
    "# Play the AWG sequence that contains the trigger signal.\n",
    "# Basically, this call indirectly triggers the lock-in to start capturing data.\n",
    "awg.play()\n",
    "\n",
    "# We call this blocking function to wait \n",
    "# until the requested number of samples is captured.\n",
    "lockin.buffer.wait_until_samples_captured(sample_count)\n",
    "\n",
    "# Stop capturing.\n",
    "lockin.buffer.stop_capture()\n",
    "\n",
    "# Stop the AWG sequence playback\n",
    "awg.stop()\n",
    "\n",
    "# Retrieve the data from the buffer.\n",
    "# The returned data is a dictionary where keys are names of the variables\n",
    "# from the capture config, and values are the captured values.\n",
    "data = lockin.buffer.get_capture_data(sample_count)\n",
    "\n",
    "print(f\"The number of acquired X data points is {len(data['X'])}\")\n",
    "print(f\"The number of acquired Y data points is {len(data['Y'])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, the measurement code from above is encapsulated into a method of the lock-in buffer `capture_samples_after_trigger`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    \n",
    "    # Note the second argument - it is a callable\n",
    "    # that is responsible for emitting the trigger signal\n",
    "    data = lockin.buffer.capture_samples_after_trigger(sample_count, awg.play)\n",
    "    \n",
    "finally:  # the try-finally block is here purely\n",
    "          # to ensure that the AWG is stopped anyway\n",
    "    awg.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot the captured data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size to be more convenient then the defaults\n",
    "fig = plt.figure(figsize=(6, 3))\n",
    "\n",
    "# plot values of all the captured variables\n",
    "for var_name in data:\n",
    "    plt.plot(data[var_name], label=var_name)  \n",
    "plt.xlabel(\"Sample, #\")\n",
    "plt.ylabel(\"Measured value, V\")\n",
    "\n",
    "plt.legend()  # show legend\n",
    "plt.tight_layout()  # adjust the figure so that all the labels fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Capturing one sample per trigger\n",
    "\n",
    "In this example, we are going to initiate data capture that will capture one sample per received trigger signal. Lock-in amplifier SR860 reacts on the falling edge of the trigger signal. We are going to use a marker of an AWG channel to send the triggers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup AWG to emit a trigger pulse train\n",
    "\n",
    "The following code is specific to the AWG5208 that is used in this example. One is welcome to use waveform generation frameworks like `broadbean` rather than the low-level kind of interaction with the AWG driver below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "awg.sample_rate(3000)  # S/s\n",
    "\n",
    "# Create a waveform where the analog channel plays 0s,\n",
    "# while the marker channel plays \n",
    "# a number of falling edges from 1 to 0.\n",
    "\n",
    "n_samples_in_waveform = 3000\n",
    "# the waveform will have a length of 1s\n",
    "waveform_ch1 = numpy.zeros((2, n_samples_in_waveform))\n",
    "\n",
    "n_trigger_pulses = 100\n",
    "waveform_ch1[1, :] = numpy.tile(\n",
    "    numpy.concatenate((  # this defines a single trigger pulse\n",
    "                         # that represents a falling edge\n",
    "        # first half a single pulse is high (1s)\n",
    "        numpy.ones(n_samples_in_waveform//n_trigger_pulses//2),\n",
    "        # second half a single pulse is low (0s)\n",
    "        numpy.zeros(n_samples_in_waveform//n_trigger_pulses//2)\n",
    "    )),\n",
    "    n_trigger_pulses\n",
    ")  # falling from 1 to 0 (a.u.) every 0.01s after the start of the waveform\n",
    "\n",
    "elements = numpy.array([waveform_ch1])  # we only have one element in the sequence\n",
    "waveforms = numpy.array([elements])  # we will use only 1 channel\n",
    "\n",
    "# Create a sequence file from the \"waveform\" array\n",
    "seq_name = 'single_trigger_marker_1'\n",
    "seqx = awg.makeSEQXFile(\n",
    "    trig_waits=[0], nreps=[1], event_jumps=[0], event_jump_to=[0], go_to=[1],\n",
    "    wfms=waveforms, amplitudes=[1.0], seqname=seq_name)\n",
    "\n",
    "# Send the sequence file to AWG internal disk\n",
    "seqx_file_name = seq_name + '.seqx'\n",
    "awg.sendSEQXFile(seqx, seqx_file_name)\n",
    "\n",
    "awg.clearSequenceList()\n",
    "awg.clearWaveformList()\n",
    "\n",
    "# Load the sequence file\n",
    "awg.loadSEQXFile(seqx_file_name)\n",
    "\n",
    "# Full resolution of the AWG channel is 16 bits for AWG5208,\n",
    "# but we take 1 bit for the marker channel\n",
    "awg.ch1.resolution = 16 - 1\n",
    "\n",
    "awg.ch1.awg_amplitude(1)  # V\n",
    "# Load a particular sequence to the channel\n",
    "awg.ch1.setSequenceTrack(seq_name, 0)\n",
    "# Assign a waveform to the channel\n",
    "awg.ch1.setWaveform(awg.waveformList[0])\n",
    "\n",
    "# Set the marker's high as high as possible \n",
    "# so that the lock-in detects the falling edge\n",
    "awg.ch1.marker1_high(1.75)  # V\n",
    "awg.ch1.marker1_low(0)  # V\n",
    "\n",
    "awg.ch1.state(1)  # turns the channel \"on\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capture data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of acquired X data points is 100\n",
      "The number of acquired Y data points is 100\n"
     ]
    }
   ],
   "source": [
    "sample_count = n_trigger_pulses\n",
    "\n",
    "# Set the capture length (which is a portion of the buffer size) \n",
    "# to fit the number of samples that we want to acquire.\n",
    "# For more information about the maximum buffer size, \n",
    "# and other buffer-related properties, refer to the instrument manual.\n",
    "lockin.buffer.set_capture_length_to_fit_samples(sample_count)\n",
    "\n",
    "# Start capturing data, and capture one sample per each received trigger signal.\n",
    "# This basically arms the lock-in amplifier.\n",
    "# For more information about the capture modes, refer to the instrument manual.\n",
    "lockin.buffer.start_capture(\"ONE\", \"TRIG\")\n",
    "\n",
    "# Play the AWG sequence that contains the trigger pulses train.\n",
    "awg.play()\n",
    "\n",
    "# We call this blocking function to wait\n",
    "# until the requested number of samples is captured.\n",
    "lockin.buffer.wait_until_samples_captured(sample_count)\n",
    "\n",
    "# Stop capturing.\n",
    "lockin.buffer.stop_capture()\n",
    "\n",
    "# Stop the AWG sequence playback\n",
    "awg.stop()\n",
    "\n",
    "# Retrieve the data from the buffer.\n",
    "# The returned data is a dictionary where keys are names of the variables\n",
    "# from the capture config, and values are the captured values.\n",
    "data = lockin.buffer.get_capture_data(sample_count)\n",
    "\n",
    "print(f\"The number of acquired X data points is {len(data['X'])}\")\n",
    "print(f\"The number of acquired Y data points is {len(data['Y'])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, the measurement code from above is encapsulated into a method of the lock-in buffer `capture_one_sample_per_trigger`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    \n",
    "    # Note the second argument - it is a callable \n",
    "    # that is responsible for starting the trigger pulse train\n",
    "    data = lockin.buffer.capture_one_sample_per_trigger(sample_count, awg.play)\n",
    "    \n",
    "finally:  # the try-finally block is here purely \n",
    "          # to ensure that the AWG is stopped anyway\n",
    "    awg.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot the captured data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size to be more convenient then the defaults\n",
    "fig = plt.figure(figsize=(6, 3))\n",
    "\n",
    "# plot values of all the captured variables\n",
    "for var_name in data:\n",
    "    plt.plot(data[var_name], label=var_name)\n",
    "plt.xlabel(\"Sample, #\")\n",
    "plt.ylabel(\"Measured value, V\")\n",
    "\n",
    "plt.legend()  # show legend\n",
    "plt.tight_layout()  # adjust the figure so that all the labels fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  },
  "nbsphinx": {
   "execute": "never"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "247px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}